Zhong et al.  [1]} treats weakly supervised video anomaly detection as a label noise learning task. However, the extreme label noise results from assigning video-level labels to each clip. In contrast, MIST offers pseudo labels with lower noise via multiple instance generator, which is more efficient. Additionally, MIST can further co-operate with label noise learning methods to refine pseudo labels iteratively and train a more powerful feature encoder.
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